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Analysis and predictions of CO2 emissions using Neural Networks

Vyas, Jeet Jaikishan (2021) Analysis and predictions of CO2 emissions using Neural Networks. Masters thesis, Dublin, National College of Ireland.

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The research is broadly focused on analyzing how the CO2 emissions and Age dependency ratio indicators showcase the effects on an overall development of certain countries. The data has been fetched from World Bank and world health organisation (WHO) originally and manually was put together to be available on Kaggle. The aim is to understand how this can give a broad insight on the historical and trends on the development prospects of the particular country. The indicators targeted here are in the employment and environment sectors. The indicators are “Age Dependency Ratio” & “Carbon-dioxide Emissions” quoted as CO2 emissions. Research purely focuses on achieving a comparative study on the models and analysis on the behavior and trends of the indicators for a span of 55 years. Models created using neural networks and time series predictions. Analyzing the indicators and predicting the CO2 emissions using economic and CO2 emission indicators. A comparative, analytical and predictive study will be achieved.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
H Social Sciences > HC Economic History and Conditions > Development Economics
G Geography. Anthropology. Recreation > GE Environmental Sciences > Environment
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 14 Mar 2023 14:24
Last Modified: 14 Mar 2023 14:24

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